Embodiments according to the invention are related to a transmission filter calculator, a method for calculating a transmission filter, a communication device, a method for operating a communication device and to computer programs.
An embodiment according to the invention is related to an adaptive unitary precoding for multicell multiple-input-multiple-output (MIMO) communications.
Embodiments according to the invention are useable in the field of wireless communications. Further embodiments according to the invention are related to the field of transmission technology. Some embodiments according to the invention are related to the field of cooperative multi-point (CoMP) transmission. Some embodiments according to the invention are related to the field of orthogonal beamforming. Some embodiments according to the invention are related to a MIMO downlink.
In the following, some application scenarios which occur in current communication networks like, for example, mobile communication networks, will be described. In particular, a target configuration in which embodiments according to the invention can be advantageously applied will be described.
In many communication environments there are multiple users in a multicell/cooperative multi-point (CoMP) system.
One of the challenges in such a system is the downlink transmission in the multiuser multicell/CoMP system. In this case, there is a so-called “interference network”. For example, there is a very significant interference level due to the presence of multiple base stations (and possibly also multiple mobile stations). Also, advanced multiple-input-multiple-output transmission is often applied in such systems, which increases the complexity. Furthermore, there is often unknown inter-cell interferences, which also makes it more difficult to choose proper communication parameters.
A graphical representation of a typical communication environment, in which embodiments according to the present invention may be applied, is shown in FIG. 1.
In view of such communication environments, it is a goal to reduce uncertainty in interference to obtain more robust downlink strategies.
Moreover, it should be noted that cell-edge users experience inter-cell interference in many modern communication environments. Inter-cell interference of mobile communication devices which are in the proximity of a cell-edge are shown in FIG. 2, which shows a graphical representation of such a scenario.
It has been found that for MIMO transmission, the spatial signature of the interference is typically unknown. It has also been found that this causes problems for link adaptation and algorithmic impairments in higher layers (like, for example, scheduler and resource allocation, for example fractional reuse).
In view of this situation, it is a goal to have robust MIMO downlink strategies and to solve the above mentioned problems.
In the following, some alternative solutions will be described.
For example, a so-called “codebook-based MIMO” concept may be used. An example of such a concept is known as “PU2RC”. In this concept, a unitary codebook makes interference well-predictable. However, it has been found that said concept does not exploit the full capabilities a of multiuser multiple-input-multiple-output approach.
Another alternative solution is the so-called “advanced multiuser MIMO” (also briefly designated as “MU-MIMO”). This concept uses an adaptive precoding. Moreover, low complexity solutions are available like, for example, a solution called “SESAM” (see, for example, reference [B3]) and a solution called “LISA” (see, for example, reference [B4]). In this advanced multiuser MIMO, robustness is typically achieved either by a second pilot (which constitutes an additional overhead) or by conservative rate adaptation (which brings along a performance loss). For details, reference is made to reference [B1]).
However, it has been found that codebook based approaches do not exploit the full potential of MU-MIMO. Moreover, it has been found that robustness for adaptive MIMO causes additional overhead in alternative implementations. Also, it has been recognized that it is difficult to find optimal receivers, which has a huge impact on performance. Thus, it can be seen that alternative solutions comprise a number of problems and limitations.
In the following, some recent advances will be briefly summarized.
Several concepts for adaptive unitary precoding have been found. For example, references is made to documents [B6] to [B10]. The concepts use adaptive precoding and it has been found that interference is well predictable. However, an optimal solution is not available for linear precoding. Also, it has been found that it is difficult to optimize (for example, because the optimization problem is non-convex and combinatorial). Moreover, it has been found that low complexity solutions are only available for single antenna receivers.
In view of the above discussion, it is an object of the present invention to create an efficient concept for communicating in a multicell multi-input-multi-output communication environment.